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Sensors and Materials
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Sensors and Materials, Volume 31, Number 12(2) (2019)
Copyright(C) MYU K.K.
pp. 4061-4068
S&M2069 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2019.2452
Published: December 16, 2019

Method of Estimating Heatstroke Risk Using Wristwatch-type Device [PDF]

Yoshiyuki Kaiho, Seiichi Takamatsu, and Toshihito Itoh

(Received May 31, 2019; Accepted September 10, 2019)

Keywords: heatstroke, WBGT, black globe temperature, neural network, wearable device

As a method of estimating the risk of heatstroke with a wearable device, we have developed a method of calculating the wet bulb globe temperature (WBGT) by estimating the black globe temperature (Tg) only from sensors that can be mounted on a wristwatch-type device. In WBGT measurement, the conventional method requires a large sensor for measuring Tg, and it has been difficult to grasp an individual’s heatstroke risk. In this research, we proposed a method of estimating Tg using a neural network and compared the estimation accuracy for different numbers of layers and nodes. In the Tg range of 31 to 41 ℃, it was confirmed that when Tg was estimated by the fully connected neural network of three layers and 20 nodes, the regression coefficient between the measured Tg and the estimated Tg was 0.90, indicating a high accuracy.

Corresponding author: Yoshiyuki Kaiho


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Cite this article
Yoshiyuki Kaiho, Seiichi Takamatsu, and Toshihito Itoh, Method of Estimating Heatstroke Risk Using Wristwatch-type Device, Sens. Mater., Vol. 31, No. 12, 2019, p. 4061-4068.



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